IEEE Transactions on Information Theory最新文献

{"title":"Another Infinite Family of Binary Cyclic Codes With Best Parameters Known","authors":"Yansheng Wu;Zhonghua Sun;Cunsheng Ding","doi":"10.1109/TIT.2023.3310500","DOIUrl":"10.1109/TIT.2023.3310500","url":null,"abstract":"Cyclic codes are important in theory, as they are closely related to a number of areas of mathematics. Cyclic codes are also important in practice, as they have efficient encoding and decoding algorithms. An infinite family of cyclic codes over \u0000<inline-formula> <tex-math>${mathrm {GF}}(q)$ </tex-math></inline-formula>\u0000 is said to have linearly-best-known parameters if for any \u0000<inline-formula> <tex-math>$[n, k, d]$ </tex-math></inline-formula>\u0000 code \u0000<inline-formula> <tex-math>${mathcal {C}}$ </tex-math></inline-formula>\u0000 in this family, there is no known \u0000<inline-formula> <tex-math>$[n, k, d']$ </tex-math></inline-formula>\u0000 linear code over \u0000<inline-formula> <tex-math>${mathrm {GF}}(q)$ </tex-math></inline-formula>\u0000 such that \u0000<inline-formula> <tex-math>$d' &gt; d$ </tex-math></inline-formula>\u0000. An infinite family of cyclic codes over \u0000<inline-formula> <tex-math>${mathrm {GF}}(q)$ </tex-math></inline-formula>\u0000 is said to have cyclicly-best-known parameters if for any \u0000<inline-formula> <tex-math>$[n, k, d]$ </tex-math></inline-formula>\u0000 code \u0000<inline-formula> <tex-math>${mathcal {C}}$ </tex-math></inline-formula>\u0000 in this family, there is no known \u0000<inline-formula> <tex-math>$[n, k, d']$ </tex-math></inline-formula>\u0000 cyclic code over \u0000<inline-formula> <tex-math>${mathrm {GF}}(q)$ </tex-math></inline-formula>\u0000 such that \u0000<inline-formula> <tex-math>$d' &gt; d$ </tex-math></inline-formula>\u0000. It is very rare to see an infinite family of binary cyclic codes with cyclicly-best-known parameters whose duals codes have also cyclicly-best-known parameters. The objective of this paper is to study such family of binary cyclic codes of length \u0000<inline-formula> <tex-math>$2^{m}-1$ </tex-math></inline-formula>\u0000 and dimension \u0000<inline-formula> <tex-math>$2^{m}-1-m(m-1)/2$ </tex-math></inline-formula>\u0000, denoted by \u0000<inline-formula> <tex-math>${mathcal {C}}_{(2,m,2)}$ </tex-math></inline-formula>\u0000, and their dual codes \u0000<inline-formula> <tex-math>${mathcal {C}}_{(2,m,2)}^{perp} $ </tex-math></inline-formula>\u0000. The weight distribution of \u0000<inline-formula> <tex-math>${mathcal {C}}_{(2,m,2)}^{perp} $ </tex-math></inline-formula>\u0000 is settled and the parameters of \u0000<inline-formula> <tex-math>${mathcal {C}}_{(2,m,2)}$ </tex-math></inline-formula>\u0000 are investigated in this paper. A larger family of binary cyclic codes \u0000<inline-formula> <tex-math>${mathcal {C}}_{(2,m,r)}$ </tex-math></inline-formula>\u0000 and their duals are also constructed and studied in this paper, where \u0000<inline-formula> <tex-math>$0 leq r leq m-1$ </tex-math></inline-formula>\u0000.","PeriodicalId":13494,"journal":{"name":"IEEE Transactions on Information Theory","volume":"70 6","pages":"4110-4116"},"PeriodicalIF":2.5,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62929175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Few Interactions Improve Distributed Nonparametric Estimation, Optimally","authors":"Jingbo Liu","doi":"10.1109/TIT.2023.3309920","DOIUrl":"10.1109/TIT.2023.3309920","url":null,"abstract":"Consider the problem of nonparametric estimation of an unknown \u0000<inline-formula> <tex-math>$beta $ </tex-math></inline-formula>\u0000-Hölder smooth density \u0000<inline-formula> <tex-math>$p_{XY}$ </tex-math></inline-formula>\u0000 at a given point, where \u0000<inline-formula> <tex-math>$X$ </tex-math></inline-formula>\u0000 and \u0000<inline-formula> <tex-math>$Y$ </tex-math></inline-formula>\u0000 are both \u0000<inline-formula> <tex-math>$d$ </tex-math></inline-formula>\u0000 dimensional. An infinite sequence of i.i.d. samples \u0000<inline-formula> <tex-math>$(X_{i},Y_{i})$ </tex-math></inline-formula>\u0000 are generated according to this distribution, and two terminals observe \u0000<inline-formula> <tex-math>$(X_{i})$ </tex-math></inline-formula>\u0000 and \u0000<inline-formula> <tex-math>$(Y_{i})$ </tex-math></inline-formula>\u0000, respectively. They are allowed to exchange \u0000<inline-formula> <tex-math>$k$ </tex-math></inline-formula>\u0000 bits either in oneway or interactively in order for Bob to estimate the unknown density. We show that the minimax mean square risk is order \u0000<inline-formula> <tex-math>$left ({frac {k}{log k} }right)^{-frac {2beta }{d+2beta }}$ </tex-math></inline-formula>\u0000 for one-way protocols and \u0000<inline-formula> <tex-math>$k^{-frac {2beta }{d+2beta }}$ </tex-math></inline-formula>\u0000 for interactive protocols. The logarithmic improvement is nonexistent in the parametric counterparts, and therefore can be regarded as a consequence of nonparametric nature of the problem. Moreover, a few rounds of interactions achieve the interactive minimax rate: the number of rounds can grow as slowly as the super-logarithm (i.e., inverse tetration) of \u0000<inline-formula> <tex-math>$k$ </tex-math></inline-formula>\u0000. The proof of the upper bound is based on a novel multi-round scheme for estimating the joint distribution of a pair of biased Bernoulli variables, and the lower bound is built on a sharp estimate of a symmetric strong data processing constant for biased Bernoulli variables.","PeriodicalId":13494,"journal":{"name":"IEEE Transactions on Information Theory","volume":"69 12","pages":"7867-7886"},"PeriodicalIF":2.5,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10234708","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74247287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Infinite Family of Binary Cyclic Codes With Best Parameters","authors":"Zhonghua Sun;Chengju Li;Cunsheng Ding","doi":"10.1109/TIT.2023.3307732","DOIUrl":"10.1109/TIT.2023.3307732","url":null,"abstract":"Binary cyclic codes with parameters \u0000<inline-formula> <tex-math>$[n,(n+1)/2, dgeq sqrt {n}]$ </tex-math></inline-formula>\u0000 are very interesting, as their minimum distances have a square-root bound. The binary quadratic residue codes and the punctured binary Reed-Muller codes of order \u0000<inline-formula> <tex-math>$(m-1)/2$ </tex-math></inline-formula>\u0000 for odd \u0000<inline-formula> <tex-math>$m$ </tex-math></inline-formula>\u0000 are two infinite families of binary cyclic codes with such parameters. The objective of this paper is to present and analyse an infinite family of binary BCH codes \u0000<inline-formula> <tex-math>${mathcal {C}}(m)$ </tex-math></inline-formula>\u0000 with parameters \u0000<inline-formula> <tex-math>$[2^{m}-1,2^{m-1},d]$ </tex-math></inline-formula>\u0000 whose minimum distance \u0000<inline-formula> <tex-math>$d$ </tex-math></inline-formula>\u0000 much exceeds the square-root bound when \u0000<inline-formula> <tex-math>$m geq 11$ </tex-math></inline-formula>\u0000 is a prime. The binary BCH code \u0000<inline-formula> <tex-math>${mathcal {C}}(3)$ </tex-math></inline-formula>\u0000 is the binary Hamming code and distance-optimal. The binary BCH code \u0000<inline-formula> <tex-math>${mathcal {C}}(5)$ </tex-math></inline-formula>\u0000 has parameters \u0000<inline-formula> <tex-math>$[{31,16,7}]$ </tex-math></inline-formula>\u0000 and is distance-almost-optimal. The binary BCH code \u0000<inline-formula> <tex-math>${mathcal {C}}(7)$ </tex-math></inline-formula>\u0000 has parameters \u0000<inline-formula> <tex-math>$[{127,64,21}]$ </tex-math></inline-formula>\u0000 and has the best known parameters. In addition, there is no known \u0000<inline-formula> <tex-math>$[2^{m}-1,2^{m-1}]$ </tex-math></inline-formula>\u0000 binary cyclic code whose minimum distance is better than the minimum distance of this binary BCH code \u0000<inline-formula> <tex-math>${mathcal {C}}(m)$ </tex-math></inline-formula>\u0000 with parameters \u0000<inline-formula> <tex-math>$[2^{m}-1,2^{m-1}]$ </tex-math></inline-formula>\u0000 for any odd prime \u0000<inline-formula> <tex-math>$m$ </tex-math></inline-formula>\u0000.","PeriodicalId":13494,"journal":{"name":"IEEE Transactions on Information Theory","volume":"70 4","pages":"2411-2418"},"PeriodicalIF":2.5,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62929116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Privacy Amplification and Decoupling Without Smoothing","authors":"Frédéric Dupuis","doi":"10.1109/TIT.2023.3301812","DOIUrl":"10.1109/TIT.2023.3301812","url":null,"abstract":"We prove an achievability result for privacy amplification and decoupling in terms of the sandwiched Rényi entropy of order \u0000<inline-formula> <tex-math>$alpha in (1,2]$ </tex-math></inline-formula>\u0000; this extends previous results which worked for \u0000<inline-formula> <tex-math>$alpha =2$ </tex-math></inline-formula>\u0000. The fact that this proof works for \u0000<inline-formula> <tex-math>$alpha $ </tex-math></inline-formula>\u0000 close to 1 means that we can bypass the smooth min-entropy in the many applications where the bound comes from the fully quantum AEP or entropy accumulation, and carry out the whole proof using the Rényi entropy, thereby easily obtaining an error exponent for the final task. This effectively replaces smoothing, which is a difficult high-dimensional optimization problem, by an optimization problem over a single real parameter \u0000<inline-formula> <tex-math>$alpha $ </tex-math></inline-formula>\u0000.","PeriodicalId":13494,"journal":{"name":"IEEE Transactions on Information Theory","volume":"69 12","pages":"7784-7792"},"PeriodicalIF":2.5,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42035341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Toward Designing Optimal Sensing Matrices for Generalized Linear Inverse Problems","authors":"Junjie Ma;Ji Xu;Arian Maleki","doi":"10.1109/TIT.2023.3307553","DOIUrl":"10.1109/TIT.2023.3307553","url":null,"abstract":"We consider an inverse problem \u0000<inline-formula> <tex-math>$boldsymbol {y}= f(boldsymbol {Ax})$ </tex-math></inline-formula>\u0000, where \u0000<inline-formula> <tex-math>$boldsymbol {x}in mathbb {R}^{n}$ </tex-math></inline-formula>\u0000 is the signal of interest, \u0000<inline-formula> <tex-math>$boldsymbol {A}$ </tex-math></inline-formula>\u0000 is the sensing matrix, \u0000<inline-formula> <tex-math>$f$ </tex-math></inline-formula>\u0000 is a nonlinear function and \u0000<inline-formula> <tex-math>$boldsymbol {y} in mathbb {R}^{m}$ </tex-math></inline-formula>\u0000 is the measurement vector. In many applications, we have some level of freedom to design the sensing matrix \u0000<inline-formula> <tex-math>$boldsymbol {A}$ </tex-math></inline-formula>\u0000, and in such circumstances we could optimize \u0000<inline-formula> <tex-math>$boldsymbol {A}$ </tex-math></inline-formula>\u0000 to achieve better reconstruction performance. As a first step towards optimal design, it is important to understand the impact of the sensing matrix on the difficulty of recovering \u0000<inline-formula> <tex-math>$boldsymbol {x}$ </tex-math></inline-formula>\u0000 from \u0000<inline-formula> <tex-math>$boldsymbol {y}$ </tex-math></inline-formula>\u0000. In this paper, we study the performance of one of the most successful recovery methods, i.e., the expectation propagation (EP) algorithm. We define a notion of spikiness for the spectrum of \u0000<inline-formula> <tex-math>$boldsymbol {A}$ </tex-math></inline-formula>\u0000 and show the importance of this measure for the performance of EP. We show that whether a spikier spectrum can hurt or help the recovery performance depends on \u0000<inline-formula> <tex-math>$f$ </tex-math></inline-formula>\u0000. Based on our framework, we are able to show that, in phase-retrieval problems, matrices with spikier spectrums are better for EP, while in 1-bit compressed sensing problems, less spiky spectrums lead to better performance. Our results unify and substantially generalize existing results that compare Gaussian and orthogonal matrices, and provide a platform towards designing optimal sensing systems.","PeriodicalId":13494,"journal":{"name":"IEEE Transactions on Information Theory","volume":"70 1","pages":"482-508"},"PeriodicalIF":2.5,"publicationDate":"2023-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47972958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"IEEE Transactions on Information Theory information for authors","authors":"","doi":"10.1109/TIT.2023.3304209","DOIUrl":"https://doi.org/10.1109/TIT.2023.3304209","url":null,"abstract":"","PeriodicalId":13494,"journal":{"name":"IEEE Transactions on Information Theory","volume":"69 9","pages":"C3-C3"},"PeriodicalIF":2.5,"publicationDate":"2023-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/18/10225323/10225378.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67937032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Systematic Approaches to Generate Reversiblizations of Markov Chains","authors":"Michael C. H. Choi;Geoffrey Wolfer","doi":"10.1109/TIT.2023.3304685","DOIUrl":"10.1109/TIT.2023.3304685","url":null,"abstract":"Given a target distribution \u0000<inline-formula> <tex-math>$pi $ </tex-math></inline-formula>\u0000 and an arbitrary Markov infinitesimal generator \u0000<inline-formula> <tex-math>$L$ </tex-math></inline-formula>\u0000 on a finite state space \u0000<inline-formula> <tex-math>$mathcal {X}$ </tex-math></inline-formula>\u0000, we develop three structured and inter-related approaches to generate new reversiblizations from \u0000<inline-formula> <tex-math>$L$ </tex-math></inline-formula>\u0000. The first approach hinges on a geometric perspective, in which we view reversiblizations as projections onto the space of \u0000<inline-formula> <tex-math>$pi $ </tex-math></inline-formula>\u0000-reversible generators under suitable information divergences such as \u0000<inline-formula> <tex-math>$f$ </tex-math></inline-formula>\u0000-divergences. With different choices of functions \u0000<inline-formula> <tex-math>$f$ </tex-math></inline-formula>\u0000, we not only recover nearly all established reversiblizations but also unravel and generate new reversiblizations. Along the way, we unveil interesting geometric results such as bisection properties, Pythagorean identities, parallelogram laws and a Markov chain counterpart of the arithmetic-geometric-harmonic mean inequality governing these reversiblizations. This further serves as motivation for introducing the notion of information centroids of a sequence of Markov chains and to give conditions for their existence and uniqueness. Building upon the first approach, we view reversiblizations as generalized means. In this second approach, we construct new reversiblizations via different natural notions of generalized means such as the Cauchy mean or the dual mean. In the third approach, we combine the recently introduced locally-balanced Markov processes framework and the notion of convex *-conjugate in the study of \u0000<inline-formula> <tex-math>$f$ </tex-math></inline-formula>\u0000-divergence. The latter offers a rich source of balancing functions to generate new reversiblizations.","PeriodicalId":13494,"journal":{"name":"IEEE Transactions on Information Theory","volume":"70 5","pages":"3145-3161"},"PeriodicalIF":2.5,"publicationDate":"2023-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10220192","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42688615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nonparametric Two-Sample Testing by Betting","authors":"Shubhanshu Shekhar;Aaditya Ramdas","doi":"10.1109/TIT.2023.3305867","DOIUrl":"10.1109/TIT.2023.3305867","url":null,"abstract":"We study the problem of designing consistent sequential two-sample tests in a nonparametric setting. Guided by the principle of testing by betting, we reframe this task into that of selecting a sequence of payoff functions that maximize the wealth of a fictitious bettor, betting against the null in a repeated game. In this setting, the relative increase in the bettor’s wealth has a precise interpretation as the measure of evidence against the null, and thus our sequential test rejects the null when the wealth crosses an appropriate threshold. We develop a general framework for setting up the betting game for two-sample testing, in which the payoffs are selected by a prediction strategy as data-driven predictable estimates of the witness function associated with the variational representation of some statistical distance measures, such as integral probability metrics (IPMs). We then formally relate the statistical properties of the test (such as consistency, type-II error exponent and expected sample size) to the regret of the corresponding prediction strategy. We construct a practical sequential two-sample test by instantiating our general strategy with the kernel-MMD metric, and demonstrate its ability to adapt to the difficulty of the unknown alternative through theoretical and empirical results. Our framework is versatile, and easily extends to other problems; we illustrate this by applying our approach to construct consistent tests for the following problems: (i) time-varying two-sample testing with non-exchangeable observations, and (ii) an abstract class of “invariant” testing problems, including symmetry and independence testing.","PeriodicalId":13494,"journal":{"name":"IEEE Transactions on Information Theory","volume":"70 2","pages":"1178-1203"},"PeriodicalIF":2.5,"publicationDate":"2023-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42814835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Matrix Reordering for Noisy Disordered Matrices: Optimality and Computationally Efficient Algorithms","authors":"T. Tony Cai;Rong Ma","doi":"10.1109/TIT.2023.3305538","DOIUrl":"10.1109/TIT.2023.3305538","url":null,"abstract":"Motivated by applications in single-cell biology and metagenomics, we investigate the problem of matrix reordering based on a noisy disordered monotone Toeplitz matrix model. We establish the fundamental statistical limit for this problem in a decision-theoretic framework and demonstrate that a constrained least squares estimator achieves the optimal rate. However, due to its computational complexity, we analyze a popular polynomial-time algorithm, spectral seriation, and show that it is suboptimal. To address this, we propose a novel polynomial-time adaptive sorting algorithm with guaranteed performance improvement. Simulations and analyses of two real single-cell RNA sequencing datasets demonstrate the superiority of our algorithm over existing methods.","PeriodicalId":13494,"journal":{"name":"IEEE Transactions on Information Theory","volume":"70 1","pages":"509-531"},"PeriodicalIF":2.5,"publicationDate":"2023-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47829592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Theoretical Framework for Relative Localization","authors":"Xiao Shen;Lingwei Xu;Yuanpeng Liu;Yuan Shen","doi":"10.1109/TIT.2023.3305199","DOIUrl":"10.1109/TIT.2023.3305199","url":null,"abstract":"Exploring the relative positions is a key issue in many emerging location-aware applications such as autonomous driving and formation control, where there exists no infrastructure to provide the absolute position information. In this paper, we establish a theoretical framework to address the state estimation problems in relative localization networks. In particular, we introduce the relative error for state estimates based on the concept of the equivalent state class, and apply the Fisher information analysis to derive the performance bounds. Then we present how measurement uncertainties influence the performance limits in the relative localization networks with self-measurements, after which our framework is extended to the scenarios with clock asynchronization and temporal cooperation. Finally, the connection between the theoretical foundation and the algorithm design is illustrated to provide insights into the operations in practical relative localization networks.","PeriodicalId":13494,"journal":{"name":"IEEE Transactions on Information Theory","volume":"70 1","pages":"735-762"},"PeriodicalIF":2.5,"publicationDate":"2023-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62928897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}